标题： 通过组合几何变换验证视觉控制器 显示英文标题

标题： Verification of Visual Controllers via Compositional Geometric Transformations

摘要： 基于感知的神经网络控制器在依赖视觉输入在现实世界中运行的自主系统中被越来越多地使用。 在不确定性下确保此类系统的安全性具有挑战性。 现有的验证技术通常关注像素空间中的Lp有界扰动，这无法捕捉许多现实世界效应的低维结构。 在本工作中，我们引入了一种新颖的验证框架，用于基于感知的控制器，该框架可以通过用几何扰动显式建模不确定观测来生成可达集的外逼近。 我们的方法构建了一个从状态到图像的可界定映射，使得可以在考虑感知不确定性的情况下使用基于状态的验证工具。 我们提供了对方法可靠性的理论保证，并在基准控制环境中展示了其有效性。 这项工作为在现实视觉扰动下认证感知驱动控制系统的安全性提供了一个系统的方法框架。 显示英文摘要

摘要： Perception-based neural network controllers are increasingly used in autonomous systems that rely on visual inputs to operate in the real world. Ensuring the safety of such systems under uncertainty is challenging. Existing verification techniques typically focus on Lp-bounded perturbations in the pixel space, which fails to capture the low-dimensional structure of many real-world effects. In this work, we introduce a novel verification framework for perception-based controllers that can generate outer-approximations of reachable sets through explicitly modeling uncertain observations with geometric perturbations. Our approach constructs a boundable mapping from states to images, enabling the use of state-based verification tools while accounting for uncertainty in perception. We provide theoretical guarantees on the soundness of our method and demonstrate its effectiveness across benchmark control environments. This work provides a principled framework for certifying the safety of perception-driven control systems under realistic visual perturbations.